Job Description
Job Description
Our client works at the intersection of AI and physical systems, and they are hiring new grads for raw ability rather than domain experience. The role is deliberately broad: machine learning, geometry, graphics, and AI, spanning geometry and data pipelines, evaluation harnesses, internal tooling, and training and experiment support. They want real strength in one of those areas and curiosity about the rest.
What will you be doing?
- Build and maintain geometry and data pipelines. Parse CAD, convert formats, extract features, and verify that what comes out matches what went in.
- Write the evaluation harnesses and tooling that tell the team whether a model actually got better.
- Support training and experiment runs. Instrument them, debug failures, and turn results into something readable at a glance.
- Build internal tools that remove friction for everyone else.
- Take well-scoped pieces of larger research and engineering efforts, then grow your scope as you earn it.
Dealbreaker
Work experience
- Experience with ML training, data pipelines, or internal tooling
- Internships or research at organizations with a high hiring bar: top aerospace, automotive, or robotics companies, leading AI research labs, or major tech companies, or a lab affiliation
Education
- BS or MS in CS, engineering, math, physics, or a related technical field, from a highly competitive, top-tier program
Hard skills
- Proficient in Python and/or C/C++
Baseline
Seniority
- 0–2 years of experience (ONLY) in software engineering, including internships and research
Miscellaneous
- Willing to start as a generalist before specializing
Nice-to-have
Hard skills
- Exposure to one of four adjacent domains: CAD, robotics, perception, or graphics and game design. Coursework or projects count; depth is not expected.